Llama 3.3 70B vs Llama 4 Maverick 17B Instruct FP8
Llama 3.3 70B (2025) and Llama 4 Maverick 17B Instruct FP8 (2025) are compact production models from AI at Meta. Llama 3.3 70B ships a 8K-token context window, while Llama 4 Maverick 17B Instruct FP8 ships a 1M-token context window. On pricing, Llama 4 Maverick 17B Instruct FP8 costs $0.15/1M input tokens versus $0.9/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
Llama 4 Maverick 17B Instruct FP8 is ~500% cheaper at $0.15/1M; pay for Llama 3.3 70B only for vision-heavy evaluation.
Decision scorecard
Local evidence first| Signal | Llama 3.3 70B | Llama 4 Maverick 17B Instruct FP8 |
|---|---|---|
| Decision fit | Agents, Vision, and Classification | RAG, Agents, and Long context |
| Context window | 8K | 1M |
| Cheapest output | $0.9/1M tokens | $0.6/1M tokens |
| Provider routes | 1 tracked | 7 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Llama 3.3 70B uniquely exposes Vision, Multimodal, and Function calling in local model data.
- Local decision data tags Llama 3.3 70B for Agents, Vision, and Classification.
- Llama 4 Maverick 17B Instruct FP8 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Llama 4 Maverick 17B Instruct FP8 has the lower cheapest tracked output price at $0.6/1M tokens.
- Llama 4 Maverick 17B Instruct FP8 has broader tracked provider coverage for fallback and procurement flexibility.
- Llama 4 Maverick 17B Instruct FP8 uniquely exposes Structured outputs in local model data.
- Local decision data tags Llama 4 Maverick 17B Instruct FP8 for RAG, Agents, and Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
Llama 3.3 70B
$945
Cheapest tracked route: Fireworks AI
Llama 4 Maverick 17B Instruct FP8
$270
Cheapest tracked route: OpenRouter
Estimated monthly gap: $675. Batch, cache, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on Fireworks AI; start route-level A/B tests there.
- Llama 4 Maverick 17B Instruct FP8 is $0.3/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision, Multimodal, and Function calling before moving production traffic.
- Llama 4 Maverick 17B Instruct FP8 adds Structured outputs in local capability data.
- Provider overlap exists on Fireworks AI; start route-level A/B tests there.
- Llama 3.3 70B is $0.3/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Structured outputs before moving production traffic.
- Llama 3.3 70B adds Vision, Multimodal, and Function calling in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-12-09 | 2025-04-05 |
| Context window | 8K | 1M |
| Parameters | 70B | 17B |
| Architecture | decoder only | mixture of experts |
| License | True | Open Source |
| Knowledge cutoff | 2024-12 | - |
Pricing and availability
| Pricing attribute | Llama 3.3 70B | Llama 4 Maverick 17B Instruct FP8 |
|---|---|---|
| Input price | $0.9/1M tokens | $0.15/1M tokens |
| Output price | $0.9/1M tokens | $0.6/1M tokens |
| Providers |
Capabilities
| Capability | Llama 3.3 70B | Llama 4 Maverick 17B Instruct FP8 |
|---|---|---|
| Vision | Yes | No |
| Multimodal | Yes | No |
| Reasoning | No | No |
| Function calling | Yes | No |
| Tool use | Yes | No |
| Structured outputs | No | Yes |
| Code execution | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on vision: Llama 3.3 70B, multimodal input: Llama 3.3 70B, function calling: Llama 3.3 70B, tool use: Llama 3.3 70B, and structured outputs: Llama 4 Maverick 17B Instruct FP8. Both models share the core language-model surface, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, Llama 3.3 70B lists $0.9/1M input and $0.9/1M output tokens, while Llama 4 Maverick 17B Instruct FP8 lists $0.15/1M input and $0.6/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 4 Maverick 17B Instruct FP8 lower by about $0.61 per million blended tokens. Availability is 1 providers versus 7, so concentration risk also matters.
Choose Llama 3.3 70B when vision-heavy evaluation are central to the workload. Choose Llama 4 Maverick 17B Instruct FP8 when long-context analysis, larger context windows, and lower input-token cost are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, Llama 3.3 70B or Llama 4 Maverick 17B Instruct FP8?
Llama 4 Maverick 17B Instruct FP8 supports 1M tokens, while Llama 3.3 70B supports 8K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Llama 3.3 70B or Llama 4 Maverick 17B Instruct FP8?
Llama 4 Maverick 17B Instruct FP8 is cheaper on tracked token pricing. Llama 3.3 70B costs $0.9/1M input and $0.9/1M output tokens. Llama 4 Maverick 17B Instruct FP8 costs $0.15/1M input and $0.6/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Llama 3.3 70B or Llama 4 Maverick 17B Instruct FP8 open source?
Llama 3.3 70B is listed under True. Llama 4 Maverick 17B Instruct FP8 is listed under Open Source. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for vision, Llama 3.3 70B or Llama 4 Maverick 17B Instruct FP8?
Llama 3.3 70B has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for multimodal input, Llama 3.3 70B or Llama 4 Maverick 17B Instruct FP8?
Llama 3.3 70B has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Llama 3.3 70B and Llama 4 Maverick 17B Instruct FP8?
Llama 3.3 70B is available on Fireworks AI. Llama 4 Maverick 17B Instruct FP8 is available on Microsoft Foundry, Together AI, OpenRouter, Fireworks AI, and DeepInfra. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.